[{"data":1,"prerenderedAt":188},["ShallowReactive",2],{"articles-index-ja":3},[4],{"id":5,"title":6,"author":7,"body":8,"category":165,"codeHighlight":166,"cover":167,"description":170,"draft":171,"excerpt":172,"extension":173,"gallery":174,"locale":175,"meta":176,"navigation":166,"path":177,"publishedAt":178,"readingTime":135,"related":179,"seo":181,"stem":183,"tags":184,"toc":166,"updatedAt":178,"__hash__":187},"articles\u002Farticles\u002Fja\u002Fai-product-workflow.md","実践的な AI 製品開発プロセス","YHTEK",{"type":9,"value":10,"toc":162},"minimark",[11,15,19,25,31,97,151,158],[12,13,14],"h2",{"id":14},"業務フロー",[16,17,18],"p",{},"AI 製品開発はプロンプトの作成だけではありません。各工程をつなぐ運用モデルです。",[20,21,22],"blockquote",{},[16,23,24],{},"目標は速さだけではなく、明確な製品判断と検証を伴う迅速な提供です。",[26,27,28],"callout",{},[16,29,30],{},"AI は曖昧さを減らすために使い、責任を省略するためには使いません。",[32,33,38],"pre",{"className":34,"code":35,"language":36,"meta":37,"style":37},"language-ts shiki shiki-themes github-light github-dark","export const workflow = ['Idea', 'Research', 'Figma', 'Codex', 'GitHub', 'Cloud Run']\n","ts","",[39,40,41],"code",{"__ignoreMap":37},[42,43,46,50,53,57,60,64,68,71,74,76,79,81,84,86,89,91,94],"span",{"class":44,"line":45},"line",1,[42,47,49],{"class":48},"szBVR","export",[42,51,52],{"class":48}," const",[42,54,56],{"class":55},"sj4cs"," workflow",[42,58,59],{"class":48}," =",[42,61,63],{"class":62},"sVt8B"," [",[42,65,67],{"class":66},"sZZnC","'Idea'",[42,69,70],{"class":62},", ",[42,72,73],{"class":66},"'Research'",[42,75,70],{"class":62},[42,77,78],{"class":66},"'Figma'",[42,80,70],{"class":62},[42,82,83],{"class":66},"'Codex'",[42,85,70],{"class":62},[42,87,88],{"class":66},"'GitHub'",[42,90,70],{"class":62},[42,92,93],{"class":66},"'Cloud Run'",[42,95,96],{"class":62},"]\n",[32,98,102],{"className":99,"code":100,"language":101,"meta":37,"style":37},"language-mermaid shiki shiki-themes github-light github-dark","flowchart TD\n  Idea --> Research\n  Research --> Strategy\n  Strategy --> Figma\n  Figma --> Codex\n  Codex --> GitHub\n  GitHub --> CloudRun[Cloud Run]\n  CloudRun --> Iteration\n","mermaid",[39,103,104,109,115,121,127,133,139,145],{"__ignoreMap":37},[42,105,106],{"class":44,"line":45},[42,107,108],{},"flowchart TD\n",[42,110,112],{"class":44,"line":111},2,[42,113,114],{},"  Idea --> Research\n",[42,116,118],{"class":44,"line":117},3,[42,119,120],{},"  Research --> Strategy\n",[42,122,124],{"class":44,"line":123},4,[42,125,126],{},"  Strategy --> Figma\n",[42,128,130],{"class":44,"line":129},5,[42,131,132],{},"  Figma --> Codex\n",[42,134,136],{"class":44,"line":135},6,[42,137,138],{},"  Codex --> GitHub\n",[42,140,142],{"class":44,"line":141},7,[42,143,144],{},"  GitHub --> CloudRun[Cloud Run]\n",[42,146,148],{"class":44,"line":147},8,[42,149,150],{},"  CloudRun --> Iteration\n",[16,152,153,154,157],{},"製品の進捗を ",[39,155,156],{},"validated learning \u002F sprint","（スプリント当たりの検証済み学習）として表現できます。",[159,160,161],"style",{},"html pre.shiki code .szBVR, html code.shiki .szBVR{--shiki-default:#D73A49;--shiki-dark:#F97583}html pre.shiki code .sj4cs, html code.shiki .sj4cs{--shiki-default:#005CC5;--shiki-dark:#79B8FF}html pre.shiki code .sVt8B, html code.shiki .sVt8B{--shiki-default:#24292E;--shiki-dark:#E1E4E8}html pre.shiki code .sZZnC, html code.shiki .sZZnC{--shiki-default:#032F62;--shiki-dark:#9ECBFF}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":37,"searchDepth":111,"depth":111,"links":163},[164],{"id":14,"depth":111,"text":14},"AI 開発プロセス",true,{"src":168,"alt":169},"\u002Fimages\u002Fcontent\u002Farticle-ai-workflow.svg","AI 開発プロセスの記事イメージ","調査、戦略、Figma、Codex、GitHub、Cloud Run を再現可能な製品開発プロセスにつなぐ方法。",false,null,"md",[],"ja",{},"\u002Farticles\u002Fja\u002Fai-product-workflow","2026-07-10",[180],"\u002Fja\u002Fprojects\u002Fai-product-studio-platform",{"title":6,"description":182},"製品アイデアから導入まで AI を活用する実践的なプロセス。","articles\u002Fja\u002Fai-product-workflow",[185,14,186],"AI","製品開発","-xny0U2PTwI0mKTebJ41ZtKe0TuZtXeJa2y7JjVre9k",1791799799762]